The demand for high-speed and low-latency wireless communication capabilities has increased dramatically in recent years. It has been projected that by the year 2020, the volume of wireless traffic will rise to about one thousand (1000) times that of the year 2010. Supporting these traffic demands will be a challenge for future wireless networks. One challenge will be supporting the huge number of wireless devices with ever-growing demands for higher data rates within the allocated spectrum. Another will be the scheduling delay that is expected to accompany large numbers of coexisting wireless devices competing for network service and to significantly deteriorate the user experience in many delay-sensitive applications. Some network users have already started to feel the impact of such delays in places such as airports, conference halls, and stadiums where it is difficult to access the wireless network with hundreds of other devices operating concurrently. Such poor user experiences may become the norm if new technologies are not introduced to deal with the predicted growth of wireless traffic, including the Internet of Things (IoT).
Several technologies have been proposed to tackle this challenge. One straightforward approach is to install more access points (APs) in a given coverage area such that each AP can service a smaller number of users or terminal devices (TDs) and therefore more traffic can be offloaded to the wired backhaul networks. However, APs that utilize the widely adopted and deployed OFDM protocols can interfer with each other when they are deployed too close together. Sophisticated interference mitigation and resource allocation algorithms may be used to enable the closely spaced APs to accommodate multiple users. For instance, in the IEEE 802.11 (WiFi) standard, the overall available spectrum is 72 MHz in the 2.4 GHz band but adjacent APs may be restricted to utilizing 22 MHz or less of the available spectrum because they may each need to operate in different spectral bands to reduce interference with each other and with the TDs. But this kind of frequency division multiplexing may hinder closely-spaced APs from fully utilizing the available spectrum and therefore supporting the predicted user demands of the future. Moreover, in such schemes, channel planning can be time-consuming and may fail altogether, either because of a lack of communication among multiple APs, or a lack of enough independent spectral bands to support the traffic demands. The system may suffer when APs are added or removed from the network because the channel planning may need to be done all over again. Femtocell networks may suffer from similar issues since the interference between macro- and femto-base stations or among multiple femto-base stations need to be coordinated and mitigated by division of the network resources, that is reducing the spectral allocation to individual users or cells. Therefore, while installing more orthogonal frequency-divisional multiplexing (OFDM) (or similar existing protocol) based access points in a given wireless coverage area may be straightforward and a suitable solution for some applications, this solution alone does not appear to scale well enough to meet the predicted growth in traffic demands of future wireless network capabilities.
Another possible approach is to use multiple-input-multiple-output (MIMO) techniques such as have been incorporated in some existing OFDM based schemes such as WiFi and LTE (Long Term Evolution) to improve the spectral efficiency and/or reduce the scheduling delay of wireless networks. For example, multi-user multiple-input-multiple-output (MU-MIMO) techniques are able to support multiple simultaneous transmissions. However, in addition to the difficulty in operating multiple antennas, the number of supported simultaneous transmissions is limited. Therefore, this solution alone may not be sufficient for the high network densification challenge described above. Recently, researchers have begun to investigate so-called massive MIMO techniques that use many more antennas than active terminals so that the extra antennas can help focus the wireless signal energy into smaller regions and support some level of spatial multiplexing in addition to frequency multiplexing. While the massive MIMO technique brings some unique benefits beyond the traditional MIMO system, the cost and complexity of implementing these schemes may scale up with the number of antennas, which may hinder it from being widely adopted. The principle of utilizing extra antennas also can be applied in distributed antenna systems where some additional antennas are placed close to the users. The wireless signal energy can then be focused into a small area through the coordination of the local antennas and thus the system may be able to provide high data rates for certain terminal devices. However, the complexity of the system and of coordinating the antennas grows with the system size, which may limit the scalability of this solution.